Projects

From Monitoring towards Understanding, Predicting and Managing Plankton in Changing Aquatic Ecosystems

In collaboration with Bas Ibelings, Jukka Jokela, Blake Matthews, Carlos Melian, Jaime Pitarch and Johny Wüest we developing innovative approaches to phytoplankton and lake-ecosystem monitoring and integrating data with community and ecosystem theory. The long-term goal is a correct understanding and management of water resources, the biodiversity that they harbour and the services that lake ecosystems deliver.

The first step towards understanding lake biodiversity and its drivers relies on the detection of detailed patterns in plankton community dynamics, which can be the outcome of two rival processes: environmental filtering (that results in the co-occurrence of closely related species) and resource competition (the opposite pattern, i.e. overdispersion of closely related species). This implies that plankton dynamics may be explained by deterministic processes such as species-sorting or competition. On the other hand, in many instances phytoplankton communities may just be the outcome of purely stochastic processes, as predicted by the neutral theory of biodiversity proposed by Stephen P. Hubble.

In any case, modelling and prediction strictly depend upon our ability to discern deterministic from purely stochastic processes in the assembly of phytoplankton communities over short to long periods of time and over spatial landscapes such as the vertical profile of the water column or a lake transect. Under SNSF and Eawag funding, we developed an innovative and potentially ground-braking tool for high frequency monitoring of lake phytoplankton (Aquaprobe), currently deployed in Lake Greifensee. With the aim of detecting and understanding patterns in phytoplankton community dynamics, we have designed a lake monitoring platform for the characterisation and counting of algal cells (scanning flow-cytometry), coupled with measurement of the physical water environment (multiparameter probe) and contingent meteorological conditions. The aim is to automatically and with high frequency acquire information on meteorological conditions, phytoplankton composition, diversity, abundance, phytoplankton functional traits, water physico-chemical parameters, and to monitor these parameters over the vertical profile of the water column, i.e. taking the large depth of alpine lakes into account. Aided with dedicated statistical tests and computer simulations of community assembly, we aim at describing the relationship between phytoplankton diversity, community dynamics and environmental changes.

Interactions between Biodiversity, Environmental Gradients and Emerging Pollutants in Natural Phytoplankton Communities

Lakes globally contribute to the cycle of nutrients, carbon and green-house gases and are very sensitive to environmental changes (in the local catchments and in the regional climate). Lakes are generally are among the first ecosystems to encounter novel pollutants of human origin, as a consequence of discharge form industrial, urban and agricultural settlements, or shifts between those types of impact due to changes in land use.

Lake ecosystems are increasingly exposed to a complex mixture of emerging contaminants and the final impact of these toxic mixtures on aquatic ecosystems is not well understood. Traditional risk assessment approaches fail in describing the complexity of both biodiversity and the composition of stressor mixtures.

The analysis of risk and effect require new approaches which must consider the complexity of the system, and the entity of the impact under realistic conditions. This can only be done by moving from single-compound / single-species level to the mixture-community level. Realistic environmental scenarios can potentially help disentangling the effects of fluctuating environmental conditions from the effects of pollutants (multiple stressors). Emerging environmental contaminants such as pharmaceuticals (both for human, stock and agricultural use) pose new concerns for the protection of water. Synergistic interactions are rare, however the assessment of risks associated with water-born drugs requires realistic exposure levels and a mixture toxicology approach.

Phytoplankton communities are constantly exposed to multiple anthropogenic and natural stressors which affect their health in terms of structure and function. The goal of this project is to understand the two-way interaction between phytoplankton diversity and emerging chemical stressors (whose cycle/dynamics can be affected by algal diversity and growth dynamics). We want to assess the effects of diversity levels on community resilience and the effects of pollutants on community structural and functional properties such as productivity and diversity (functional and phylogenetic). In collaboration with Luca Nizzetto, we aim at exposing phytoplankton in their natural environment to emerging chemical stressors using novel field methods, for an assessment of the community adaptive capacity and resilience.

Development of individual trait-based approaches to phytoplankton biodiversity

Which individual, community and ecosystem traits foster ecosystem resistance and resilience and which traits make ecosystems more vulnerable to external forcing and disturbance? To address this question we focus on the development and application of trait-based approaches in ecology and risk assessment to understand how individual responses scale to higher-level effects.

We aim at categorizing single organisms and their assemblages based on expressed phenotypic traits that directly respond (response-traits) to environmental changes, disturbance, pollution as well as eco-evolutionary processes like selection, competition or predation, and determine trait-environment and trait-biodiversity relationships. We approach this challenge using scanning flow-cytometry and we have identified a set of focal phytoplankton traits that respond quickly and significantly to species interactions or environmental filters. Results suggest that the description of functional diversity afforded by measured individual traits is extremely sensitive with regards to environmental change, and we are currently testing trait responses for a mixture of water pollutants such as pharmaceuticals and personal care products. Measures of functional diversity based on individual traits are important to understand the eco-evolutionary mechanisms that control diversity and functioning of natural communities, and may have a significant applied impact in the fields of biodiversity ecosystem-functioning and environmental risk assessment. Part of this research is carried out in collaboration with Carlos Melian and Thomas Ott.

Metabolism of polar organic xenobiotics in phytoplankton

Knowledge on the importance of biotransformation of polar organic compounds in organisms of the aquatic food web is essential to mechanistically link environmental exposure with toxic effects but currently rather limited.

The metabolic profiles, the enzymatic activities involved and the identity of transformation products are not known in most cases although this is necessary to determine whether the metabolism results in bioactivation or detoxification of xenobiotics. This is important for scientific derivation of environmental quality standards in the context of the water framework directive as well as the evaluation of the bioaccumulation potential for registration of new chemicals within REACH.

This project was funded in collaboration with Juliane Hollender and aims at characterising the biotransformation of polar compounds in aquatic invertebrates and determining the importance for bioaccumulation as well as the contribution to fate in the aquatic environment. Specifically, here we are interested in to what extent the bioaccumulation and biotransformation in algal communities contributes to the fate in the aquatic environment, and how important is the role of biodiversity in the compounds’ environmental persistence.

Assessing impacts of cyanobacterial blooms on aquatic environments in the context of climate change and nutrient pollution

The goal of this research project, recently funded in collaboration with Piet Spaak, is to reconstruct the history of cyanobacterial blooms and the occurrence of toxic genes from lake sediments.

We also aim at assessing the effects of cyanobacteria on locally adapted zooplankton. Knowledge about this history is crucial to predict the risk for harmful cyanobacterial blooms in the context of environmental change and their consequences for lake food webs. The formerly hyper-eutrophied lake Greifensee, Switzerland, is an ideal study site to develop the method to reconstruct cyanobacterial blooms from sediment cores.

Pollution induced evolutionary responses in toxic phytoplankton populations

Aquatic organisms are increasingly exposed to complex mixtures of emerging contaminants from urban, industrial and agricultural origins. Natural populations may evolve resistance to pollutants but how these toxic mixtures relate to the evolution of resistance traits and associated fitness costs is not well understood. Here we want to study how phytoplankton populations adapt to the “chemical world”.

We interested in the number of generations and the levels of exposure that determine evolutionary adaptation to pollutants, and what are the implications of evolved resistance for ecosystem functioning (for example primary production). Adaptation can happen at the individual level (phenotypic plasticity, selection) and then can scale up to community structure, functioning, resistance and resilience. Questions include:

do realistic environmental levels of exposure to micropollutants induce individual responses as phenotypic plasticity? How long phenotypic plasticity is maintained across generations? How long before phenotypic changes are fixed within populations under chemicals' selective pressure. In this project we attempt to experimentally evolve resistant phytoplankton strains (particularly cyanobacteria) by exposing them to water borne micropollutants in the laboratory. We focus several aspects that are of key importance to understand the evolutionary ecology of micropollutants exposure.